Fried and Robinaugh BMC Medicine(2020) 18:205
https://doi.org/10.1186/s12916-020-01668-w

EDITORIAL

Open Access

Systems all the way down: embracing
complexity in mental health research
Eiko I. Fried1*† and Donald J. Robinaugh2†

Abstract
In this editorial for the collection on complexity in mental health research, we introduce and summarize theinaugural contributions to this collection: a series of theoretical, methodological, and empirical papers that aim tochart a path forward for investigating mental health in all its complexity. A central theme emerges from thesecontributions: if we are to make genuine progress in explaining, predicting, and treating mental illness, we muststudy the systems from which psychopathology emerges. As the articles in this collection make clear, the systems
that give rise to psychopathology encompass a host of components across biological, psychological, and social
levels of analysis, intertwined in a web of complex interactions. The task of advancing our understanding of thesesystems will be a challenging one. Yet, this challenge presents a unique opportunity. From physics to ecology,
there is a rapidly evolving body of interdisciplinary research dedicated to investigating complex systems. This work
provides clear guidance for psychiatric research, opportunities for collaboration, and a set of tools and concepts
from which we can draw in our efforts to understand mental health, helping us move toward our ultimate aim of
improving the prevention and treatment of psychopathology.

Background“The crises we face are systemic in nature. To overcome those crises we need to understand how systems work. To arrive at such an understanding weneed to think systemically.” [1]Throughout the twentieth century, much of psychiatry
aspired to reductionist simplicity. Whether in the Freudian unconscious, the human genome, or dysfunctional
neurobiology, researchers sought to identify the underlying cause of the troubles faced by their patients. However, far from uncovering simple etiologies, the past
century of psychiatric research has revealed systematiccomplexity, leading to a growing recognition that mental
disorders are dauntingly complex phenomena [2, 3]. Yet,
* Correspondence: eikofried@gmail.com†Eiko I. Fried and Donald Robinaugh contributed equally to this work.
1
Department of Clinical Psychology, Leiden University, Leiden, The
Netherlands
Full list of author information is available at the end of the article

despite this growing acceptance, there has been littlechange in how we study psychopathology, and much of
our research remains stubbornly rooted in the monocausal framework. If we are to make genuine progress in
explaining, predicting, and treating mental illness, it iscritical that we embrace the complexity inherent in these
disorders in our theories, methods, and empiricalresearch.
In this collection, we present a series of papers thattake up this charge. From these contributions, a central
theme emerges: mental disorders arise from a host ofcomponents across biological, psychological, and sociallevels of analysis, intertwined in a web of complex interactions. To understand mental disorders, it is not sufficient to understand single components alone: we cannot
hope to understand depression from studying only theamygdala any more than we can understand the weather
by careful examination of water droplets. We must go
further and understand both the individual components
and the complex interactions among them. That is, we© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
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Fried and Robinaugh BMC Medicine(2020) 18:205

should aim to understand the systems from which psychopathology emerges.
Achieving such understanding will be no easy task.
The systems giving rise to mental illness are massively
multifactorial, and there is little evidence that any one
factor is either necessary or sufficient for any given disorder to emerge [3]. The systems exhibit both multifinality (i.e., the same set of causal agents can lead todifferent mental health outcomes) and equifinality (i.e.,
diverse causes can produce the same disorder) [4, 5].
The systems are heterogeneous, with individuals differing not only in the specific constellation of symptoms
experienced, but also in the etiological factors that precede and predict illness onset [6, 7]. Further, systems
within individuals are dynamic: they rise and fall andevolve over time.
In the six articles inaugurating this collection, researchers operating from a range of perspectives review
what we know about the systems that affect mental
health. In doing so, they chart a path forward for how
we can approach the challenging task of better understanding these complex systems, and how we can leverage that understanding to improve treatment.

Mental health and mental disorder as products ofcomplex systems
McLaughlin et al. [8] provide a review of transdiagnostic
risk and resilience factors that mediate the relationshipbetween childhood trauma exposure and psychopathology. In doing so, the authors introduce two ideas thatrun through much of this collection. First, mental disorders are multifactorial, arising from factors across biological, psychological, and social levels of analysis.
McLaughlin and colleagues highlight the role of accelerated biological aging, emotional processing, and socialinformation processing as mediators of the effect ofchildhood trauma on psychopathology, emphasizing
that, by virtue of its impact on these mediators, the same
trauma exposure can lead to a range of disorders.
Second, the authors emphasize the dynamic nature ofmental health and the need to understand how psychopathology unfolds over time, most saliently over thecourse of childhood and adolescence. McLaughlin andcolleagues persuasively argue that interrupting the evolution of these disorders by targeting transdiagnostic factors affected by childhood trauma may be critical topreventing the development of psychopathology.
Ioannidis et al. [9] further explore the effects of childhood maltreatment in an integrated overview of theneurobiological mechanisms underlying resilience. The
authors embrace a systems perspective, conceptualizing
resilience to adverse events in childhood as a product of
a complex biopsychosocial system that includes bothbottom-up (genetic and endocrinological) and top-down

Page 2 of 4(social and psychological) influences. These components
interact to drive the neurobiological changes observed
after childhood maltreatment. Ioannidis and colleagues
argue that to conceptualize and to study this system, weshould draw from the concepts and methods developedin the interdisciplinary field of complexity science. Illustrating the value of this approach, the authors identify
valuable analytic tools from complexity science that canbe used to study systems in psychiatric research, andprovide a clear conceptual framework for thinking about
resilience to childhood adversity as state-space trajectories and attractor states.
Fritz et al. [10] implement one of the suggestions byIoannidis et al. [9], using network analysis to study interrelations among psychological and environmental resilience factors for mental health, such as family supportand self-esteem, in adolescents with and without childadversity, from ages 14 to 17. The authors find that particularly during early adolescence, resilience factors show
weaker relations with each other following child adversity, potentially indicating that positive feedback loops
among resilience factors (family support → less distress→ positive self-esteem → family cohesion → family support) are disrupted. Together with McLaughlin et al. [8],Fritz and colleagues make a compelling case for interventions during childhood and adolescence that target
transdiagnostic resilience factors with the aim of preventing the emergence of psychopathology.
The contributions from McLaughlin et al. [8], Ioannidis et al. [9], and Fritz et al. [10] provide an extensive
overview of how mental disorders can emerge from the
dynamic interactions among components across levels ofanalysis. Franklin [11] further explores the concept ofemergence by shifting the focus to even more elementary components that give rise to psychological phenomena. These components, known as psychologicalprimitives, represent the fundamental and irreduciblebuilding blocks of psychological experiences, such ascore affect, exteroception, and conceptual knowledge.
Drawing heavily from constructivist accounts of emotion, Franklin argues that suicidal thoughts (and all otherpsychological phenomena) emerge from interactions
among these psychological primitives. To understandhow distinct biopsychosocial factors contribute to suicidal thoughts, Franklin argues we must understand how
they affect these constituent components, a frameworkthat suggests novel paths by which we may intervene toreduce suicidal thoughts.

Psychological treatment from a complex systems
perspective
In the two remaining inaugural contributions of the special collection, Burger et al. [12] as well as Hayes andAndrews [13] leverage a systems-perspective to informFried and Robinaugh BMC Medicine(2020) 18:205

psychotherapy research. Hayes and Andrews [13] provide an introduction of basic principles from complexity
science relevant to mental health, such as attractor states(i.e., states to which the mental health system will gravitate), early warning signals that indicate increased potential for a transition to an alternative attractor state, andnetwork destabilization: the disruption of a system stuck
in a harmful state to facilitate transitions to a new stateof mental health. Across various fields of science, eachof these concepts has been fruitfully used to explain,predict, and intervene on systems. In ecology, for example, lakes show early warning signals before theyreach a tipping point and transition into an alternative(eutrophic) stable state. Hayes and Andrews review a
growing psychiatric literature that draws on these concepts to advance our understanding of psychotherapy
and concludes by persuasively arguing that a complex
systems approach to psychotherapy is both viable andnecessary to transition psychiatry into the twenty-firstcentury.
Burger et al. [12] further embraces a complex systems
approach to psychotherapy, calling for the formalizationof a patient’s case conceptualization using computationalmodels: a tool commonly used in other areas of complexity science to represent a system and evaluate howthat system will evolve over time. Burger and colleagues
propose to extend this approach, using computationalmodels as a thinking tool to aid case conceptualizations,a didactic tool for helping patients understand the factors giving rise to their distress, a prediction tool for anticipating treatment outcomes, and a treatment selection
tool that can guide the selection of interventions most
likely to lead to change in psychotherapy. Together withHayes and Andrews [13], Burger and colleagues make acompelling argument that a systems approach can inform not only psychiatric research, but also the ongoingpractice of psychotherapy.

Conclusion
A central argument emerges from the six initial articlesof this collection: mental disorders arise from complexsystems, and our ability to explain, predict, and intervene
on mental disorders will hinge on our ability to makeprogress in understanding these systems. In just a brief
sampling from these articles, numerous systems are
identified across time scales and levels of analysis, including neurobiological systems, systems composed of
psychological primitives that give rise to momentary
instances of psychological experience, transdiagnostic
systems of risk and resilience factors that evolve
throughout adolescence, systems of interacting symptoms that harden into syndromes over months, and social support systems that may evolve over years. Thesesystems overlap, interact, and are embedded within one

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another: it is systems all the way down. Just as studying
one component is insufficient to understand the causeof a mental disorder, studying one system alone is also
unlikely to be sufficient. Accordingly, the task of understanding the systems that give rise to mental disorders
will be a challenging one.
Yet, with this challenge we bring good news. There isa large and rapidly evolving interdisciplinary body of scientific research dedicated to investigating complex systems [14]. From physics to ecology, scientific efforts
have increasingly turned toward unraveling the operation of complex systems. As demonstrated by several
articles in this collection, this interdisciplinary work provides a large toolkit from which psychiatry can draw inthe effort to understand complex systems in mental
health research. This effort calls for us to tear down artificial barriers between disciplines such as psychiatry,clinical psychology, and sociology and highlights the importance of interdisciplinary collaborations. Ultimately,embracing complexity presents both an unparalleledchallenge and, simultaneously, an enormous opportunity
to advance our understanding of mental disorders andour ability to support those who suffer from them.
Acknowledgements
None.
Authors’ contributions
EIF and DR wrote the manuscript together. Both authors read and approved
the final version.
Funding
DJR was supported by a National Institute of Mental Health Career
Development Award (1K23MH113805 - 01A1).
Availability of data and materials
Does not apply.
Ethics approval and consent to participate
Does not apply.
Consent for publication
Does not apply.
Competing interests
None.
Author details
1
Department of Clinical Psychology, Leiden University, Leiden, The
Netherlands. 2Department of Psychiatry, Harvard Medical School &Massachusetts General Hospital, Boston, MA, USA.
Received: 15 June 2020 Accepted: 15 June 2020

References
1. Hofkirtchner W, Rousseau D. Foreword to: L. von Bertalanffy. Generalsystems theory, revised edition. USA: George Braziller; 2015.
2. Bolton D. Classification and causal mechanisms: a deflationary approach tothe classification problem. Philosophical issues in psychiatry II. Nosology.
2012:6–11.
3. Kendler K. The dappled nature of causes of psychiatric illness: replacing theorganic-functional/hardware-software dichotomy with empirically based

Fried and Robinaugh BMC Medicine

4.
5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

(2020) 18:205

pluralism. Mol Psychiatry. 2012;17(4):377–88. https://doi.org/10.1038/mp.
2011.182.
Cicchetti D, Rogosch FA. Equifinality and multifinality in developmental
psychopathology. Dev Psychopathol. 1996;8(4):597–600.
Nolen-Hoeksema S, Watkins ER. A heuristic for developing transdiagnostic
models of psychopathology: explaining multifinality and divergenttrajectories. Perspect Psychol Sci. 2011;6(6):589–609. https://doi.org/10.1177/1745691611419672.
Fried EI, Nesse RM. Depression is not a consistent syndrome: aninvestigation of unique symptom patterns in the STAR*D study. J AffectDisord. 2015;172:96–102. https://doi.org/10.1016/j.jad.2014.10.010.
Kendler KS, Aggen SH. Symptoms of major depression: their stability,familiality, and prediction by genetic, temperamental, and childhood
environmental risk factors. Depression Anxiety. 2017;34(2):171–7.
McLaughlin KA, Colich NL, Rodman AM, Weissman DG. Mechanisms linking
childhood trauma exposure and psychopathology: a transdiagnostic modelof risk and resilience. BMC Med. 2020;18(1):1–11. https://doi.org/10.1186/s12916-020-01561-6.
Ioannidis K, Askelund AD, Kievit RA, Van Harmelen AL. The complex
neurobiology of resilient functioning after childhood maltreatment. BMC
Med. 2020;18(1):1–16. https://doi.org/10.1186/s12916-020-1490-7.
Fritz J, Stochl J, Fried EI, Goodyer IM, Van Borkulo CD, Wilkinson PO, vanHarmelen A-L. Unravelling the complex nature of resilience factors and theirchanges between early and later adolescence. BMC Med. 2019:1–16.
Franklin JC. Psychological primitives can make sense of biopsychosocial
factor complexity in psychopathology. BMC Med. 2019;17(1):1–8. https://doi.
org/10.1186/s12916-019-1435-1.
Burger J, Van Der Veen DC, Robinaugh DJ, Quax R, Riese H, Schoevers RA,Epskamp S. Bridging the gap between complexity science and clinicalpractice by formalizing idiographic theories: a computational model offunctional analysis. BMC Med. 2020;18(1):1–18. https://doi.org/10.1186/
s12916-020-01558-1.
Hayes, A. M., & Andrews L.: A complex systems approach to the study ofchange in psychotherapy. BMC Medicine 2020 in press. https://doi.org/10.
1186/s12916-020-01662-2.
Barabási A. The network takeover. Nat Publ Group. 2012;8(1):14–6. https://doi.org/10.1038/nphys2188.

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